EPI BRIEFING PAPERE C O N O M I C P O L I C Y I N S T I T U T E • F E B R U A R Y 2 8 , 2 0 1 3 • B R I E F I N G P A P E R # 3 5 6

ARE FOREIGN STUDENTS THE‘BEST AND BRIGHTEST’?

Data and implications forimmigration policy

B Y N O R M A N M A T L O F F

ECONOMIC POLICY INSTITUTE • 1333 H STREET, NW • SUITE 300, EAST TOWER • WASHINGTON, DC 20005 • 202.775.8810 • WWW.EPI.ORG

T A B L E O F C O N T E N T S

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Defining ‘best and brightest’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Methodology for measuring ‘best and brightest’. . . . . . . . . . . . . 5

Data for identifying and quantifying ‘best and

brightest’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Considering the effects of H-1B status on salaries. . . . . . . . . 6

Target population for the NSCG college graduate

survey data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Wage analysis of the NSCG college graduate survey data. . 8

Wage analysis using PERM data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

A look at the Microsoft salary data. . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Salary and English-language ability . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Dissertation awards among foreign and U.S. students. . . . 12

Quality of institution of doctoral study . . . . . . . . . . . . . . . . . . . . . . . . . 13

Patents awarded to American and foreign workers . . . . . . . . 14

Rates of working in R&D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Summary of the statistical analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Is there a tech labor shortage? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

The internal brain drain (‘diversion’). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Green card indenture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

H-1B and age discrimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

What should be done. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Loopholes in green card law. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Endnotes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

www.epi.org

T he technology industry, in lobbying Congress

for expansion of programs to attract skilled for-

eign workers, has long claimed that foreign

students graduating from U.S. universities in science,

technology, engineering, and mathematics are typically

“the best and the brightest,” i.e., exceptionally talented

innovators in their fields. However, the industry and its

supporters have offered little or no evidence to back up

their assertion. The claim is investigated in this report,

with a focus on former foreign students now working in

the United States, the group viewed by the industry as

key to innovation.

The assertion that the foreign graduates offer superior

skills or ability relative to U.S. graduates is found not to

be supported by the data:

On a variety of measures, the former foreign students

have talent lesser than, or equal to, their Amer-

ican peers.

Skilled-foreign-worker programs are causing an

internal brain drain in the United States.

The lack of evidence that the foreign students and work-

ers we are recruiting offer superior talent reinforces the

need to assure that programs like H-1B visa are used only

to attract the best and the brightest or to remedy genuine

labor shortages—not to serve as a source of cheap, com-

pliant labor. We must eliminate employer incentives for

using foreign workers as cheap labor, and we must end the

practice of using green card sponsorship to render foreign

workers captive to the employers who bring them into

the country.

The primary task in removing the cheap-labor incent-

ive is to reform the legal definition of prevailing wage,

which is riddled with loopholes that permit the

underpayment of H-1B workers relative to the true

market wage.

We must close the legal loopholes involving the defin-

ition of what constitutes a “qualified” worker for pur-

poses of permanent labor certification. The laws

should not force an employer to hire an American

who cannot perform the job well, but neither should

they reward employers who narrowly tailor job

requirements so that only the desired foreign applic-

ants qualify.

Everyone on either side of the high-skilled immigration

debate can agree on two axioms: (1) skilled-foreign-

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 2

worker programs should be designed to facilitate the

immigration of those who are truly talented, and (2)

immigration policy that causes the loss of America’s own

best and brightest from science, technology, engineering,

and math fields must be reversed. The findings and

recommendations in this report are designed to help make

those aspirations more concrete.

Introduction

The famous David Halberstam phrase, “the best and the

brightest,” has been used in many contexts, but perhaps

none more than to describe the foreign-national engineers

and programmers we are told the United States desper-

ately needs in order to compete in the global economy.

The debate involves the H-1B visa (which allows U.S.

employers to temporarily hire foreign workers possessing

at least a bachelor’s degree), employer-sponsored green

cards (which grant permanent residency status), and other

related facets of U.S. immigration policy. Recently the

discussion has centered on proposals to grant automatic

green cards to international students who earn advanced

STEM (science, technology, engineering, and math)

degrees at U.S. universities.

This latter group will be the major focus of this report,

which analyzes data on former foreign students who are

now working in the United States. Some are still on tem-

porary work visas, while others have been granted U.S.

permanent resident or naturalized citizen status.

The proponents of an expansive policy for foreign tech

workers contend that H-1B workers, especially those

hired from American campuses, are often “the best and

the brightest” and thus are key to the industry’s ability

to compete on the world stage. Consider, for instance

(emphasis added):

“…[restrictive U.S. immigration policy is] driving

away the world’s best and brightest”—Microsoft Chair-

man Bill Gates (Barlas 2008).

“We should not [send our] bright and talented inter-

national students…to work for our competitors

abroad upon graduation”—National Association of

Foreign Student Advisers (NAFSA 2007).

“…We should be stapling a green card to the diploma

of any foreign student who earns an advanced degree

at any U.S. university….The world’s best brains are

on sale. Let’s buy more!”—New York Times columnist

Tom Friedman (Friedman 2009).

“I personally don’t think you can have too many geni-

uses in America”—Rep. Zoe Lofgren, 1999, speak-

ing in support of automatic green cards (McCul-

lagh 1999).

Though the United States should indeed welcome the

immigration of “the world’s best brains,” are the foreign

students typically of that caliber? The tech industry has

put forth little to support such assertions. It has pointed

to some famous immigrant success stories in the field but,

in most cases, the people cited, such as Google cofounder

Sergey Brin, never held foreign-student (F-1) or work

(H-1B) visas (Brin immigrated with his parents to the

United States at age 6). And more importantly, neither

the industry nor any other participant in this national

debate has offered any empirical analysis documenting

that the visa holders are of exceptionally high talent.

This report aims to remedy this lack of data. With an eye

toward the green card proposals, it will focus mainly on

those who first entered the United States as foreign stu-

dents in computer science or electrical engineering (CS/

EE)—the two fields that make up the bulk of the H-1Bs.1

It will also look at foreign tech workers in general.

The study finds that the tech industry’s “genius” claims

for these groups are not supported by the available data.

Compared to Americans of the same education and age,

the former foreign students turn out to be weaker than, or

at most comparable to, the Americans in terms of salary,

patent applications, Ph.D. dissertation awards, and qual-

ity of the doctoral program in which they studied.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 3

For some readers of this report, perhaps the most surpris-

ing result here will concern work in research and develop-

ment (R&D). The industry has emphasized that it needs

foreign workers in order to keep its innovative edge over

other countries, yet the data show that the former foreign

students are significantly less likely to work in R&D than

the Americans.

In other words, H-1B and related programs are not raising

U.S. levels of talent and innovation in the tech fields, and are

in some ways reducing them.

These results are for the industry as a whole. There is

a perception, however, among some in Congress and by

some academics that Indian and Indian-American out-

sourcing firms operating in the United States abuse the

H-1B visa, while mainstream American firms use the visa

to hire outstanding talent (Cha 2010).2 Yet the analysis

here effectively excludes the outsourcing firms, so the

report’s findings of a lack of a best/brightest trend apply

to the mainstream firms.

Thus, the first (and main) part of this report will demon-

strate that Rep. Lofgren’s “can’t have enough geniuses”

remark was unwarranted hyperbole. But what about a

slightly modified version of Lofgren’s statement: Isn’t it

good to have as many engineers as possible, even if they

aren’t geniuses? The answer is no, because the H-1B and

green card programs have been causing an internal brain

drain of tech talent in the United States. As will be shown

here, these programs squeeze out U.S. citizens and per-

manent residents from the field and make the field unat-

tractive to this country’s most talented young domestic

students. The second part of this report will cover this

urgent issue.

Given that the foreign students are not producing a net

gain in talent level, the internal brain drain suggests that

the foreign-tech-worker programs should be reduced in

scope, not expanded. Proposals for reform are presented

in the third and final part of this report.

Defining ‘best and brightest’

We must start by defining the term, best and brightest.

This is an easy task, as the industry leaders have already

done it for us (emphasis added below):

Bill Gates (speaking in support of an expanded skilled

immigration policy):

“U.S. companies face a severe shortfall of skilled

scientists and engineers…[needed to] develop the

next generation of breakthroughs” (Gates 2008).

Intel Chairman Craig Barrett:

“By proposing a simple change in immigration

policy, EU politicians served notice that they are

serious about competing with the United States

and Asia to attract the world’s top talent to live,

work, and innovate in Europe…” (Barrett 2007).

Oracle executive Robert Hoffman:

“…America is expected to run out of its 2008

allotment of temporary (H-1B) visas for highly

educated professionals in April—before these

future innovators even graduate….It’s time for

Congress to reform our temporary and permanent

visa programs for highly skilled professionals for

one simple reason: to secure America’s innovative

position in the global economy” (Hoffman 2007).

Darla Whitaker, vice president for worldwide human

resources, Texas Instruments:

“Innovation requires innovators.…By modestly

increasing green card numbers…Congress would

ensure [America’s] place as the world’s innovation

leader” (Texas Instruments 2011).

Patrick Wilson, director of government affairs, Semi-

conductor Industry Association:

“These are real game-changing players”

(Kroll 2011).

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 4

The message is abundantly clear: What the tech industry

values are innovators, the “game changers.” Let us accord-

ingly take as our definition of best and brightest an excep-

tional level of innovative or creative talent.

Methodology for measuring ‘bestand brightest’

How should we quantify best/brightest?

Since any statistical issue is best studied from several dif-

ferent approaches, this report investigates the “best and

brightest” question using several different criteria:

high salary

high rate of patent production

Ph.D. dissertation awards

doctorate earned at a top-ranked university

employment in R&D

All of these measures should reflect the innovative abilities

prized by the tech industry.

Next is the question of the population to analyze. Many

studies are very broad in this respect, notably Hunt

(2011). Hunt’s work used the same dataset as one of those

used in this report, but we make two key restrictions:

Instead of combining all immigrants, or all foreign

workers, this report will focus mainly on immigrants

who first entered the United States as foreign stu-

dents.

Instead of combining workers from all fields, this

report will focus on those who have degrees in com-

puter science (CS) or electrical engineering (EE) and

who are working in those fields.

The CS and EE fields are of interest as they are the two

most common among foreign STEM workers, and there

is broad overlap between the two fields. Many EE gradu-

ates, for example, work as software developers. University

CS departments often have faculty with EE degrees and

vice versa.

This restriction to field is key, as there are many pitfalls

in these kinds of data. Take the field of mathematics,

for instance, at a company like Google. Some mathem-

aticians might work there as data miners, at a high salary,

while others may work as analysts of server reliability, at

a lesser salary. Yet to the unwary researcher, both types

of mathematicians would be treated as one. As a CS pro-

fessor (formerly a professor of electrical and computer

engineering) and a former Silicon Valley software

developer, the author understands the qualitative side of

the CS/EE labor market, and thus limits this analysis to it.

Unlike Hunt (2011), this report will not analyze entre-

preneurship and number of research papers published, as

the value of each of these indicators in assessing innova-

tion is problematic.

The difficulty with focusing on entrepreneurship is that

one doesn’t know what kind of business is involved.

Berkeley researcher AnnaLee Saxenian found that 36 per-

cent of the Chinese-immigrant-owned firms were in the

business of “computer wholesaling,” meaning that they

simply assembled commodity PCs, with no engineering

or programming work involved (Saxenian 1999). This

business certainly does not represent best/brightest innov-

ation. And many Indian-owned tech firms are in the

outsourcing business—again not the type of entrepren-

eurship that is relevant here.

As for counts of research papers, the consensus in aca-

demia is that such counts confuse quantity with quality,

and thus offer a poor measure of skill (Patterson, Snyder,

and Ullman 1999; Hamermesh and Pfann 2011).3 In

addition, publication rates vary widely among research

specialties, so that, for example, CS researchers in software

publish much more frequently than CS researchers in

algorithms. It is thus highly difficult to connect publica-

tion counts to innovation.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 5

Data for identifying and quantifying ‘bestand brightest’

The datasets used in this report consist of:

the 2003 National Survey of College Graduates

(NSCG), for salary, patent, and R&D analyses

the Department of Labor Program Electronic Review

Management (PERM) data, for additional salary ana-

lysis

the National Research Council (NRC) assessment of

doctoral programs, 2010, together with U.S. News

and World Report information

the Association for Computing Machinery (ACM)

Dissertation Awards.

The NSCG is a database of college graduates, in this

case individuals living in the United States during the

reference week of October 1, 2003, holding a bachelor’s

or higher degree in any field, and under age 76. It has

been used extensively by researchers (including Hunt) to

investigate a variety of issues. It is used here to assess the

impact of former foreign student status on salaries, patent

production, and R&D employment. The comparison we

make here is between former foreign students who were

working in CS/EE as of 2003 (referred to as “original

F-1 status”) and U.S. natives in the computer science and

electrical engineering fields. (In the case of salary analysis,

there will be an additional restriction, to be explained in

the next section.)

The PERM data consist of all employer-sponsored green

card applications, 2001–2011, for further salary analyses.

We use the remaining datasets to analyze the former for-

eign students in terms of dissertation awards and quality

of graduate institution.

Considering the effects of H-1B statuson salaries

In using salary analysis to assess innovative ability, one

must deal with the issue of possible underpayment of

visa workers.

The industry has vehemently denied underpaying H-1B

workers. Indeed, the question as to whether holders of the

H-1B work visa are paid less than comparable Americans

has been the subject of controversy even in the research

literature.

The law requires employers of H-1Bs and green card

sponsorees to pay the prevailing wage, defined as the aver-

age salary in a given occupation, for a given region and

a specified number of years of experience. The industry’s

denials of underpayment are technically correct; viola-

tions of the law are rare, even among Indian outsourcing

firms. However, loopholes enable underpayment of the

foreign workers relative to their true market value. For

example, the government data do not account for special

technical skill sets, or for having an advanced degree.

Previous research on CS/EE estimates the underpayment

at 15–20 percent (Matloff 2003); a study of earlier data

calculated the pay gap for engineering to be 33 percent

(Ong and Blumenthal 1997). Hunt, analyzing all college

graduates, with no restriction on field, found that the

group of interest here—those who first arrived as foreign

graduate students—were making significantly less than

comparable natives (Hunt 2009).4

On the other hand, Lofstrom and Hayes (2012) con-

cluded that the H-1Bs are at least as well paid as the

Americans, and Mithas and Lucas (2010) found that for-

eign information technology (IT) workers are paid 2.3

percent more.

A key aspect of these studies is the dataset. Mithas and

Lucas, for example, based their analysis on a reader survey

of a magazine for IT managers, not mainstream engineers

and programmers. Also, the average age in their sample

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 6

was about a decade older than among H-1Bs in general,

thus again indicating that their study may not be repres-

entative of the mainstream. Though Hunt (2009; 2011)

corrects for field of highest degree (but not current profes-

sion), her dataset is extremely broad, with unknown con-

sequences to the analyses.

Another issue is that, in attempting to determine whether

H-1Bs are paid less than comparable Americans, the key

word is comparable. The industry claims that typically

H-1Bs are hired because they possess special technological

skills that are in short supply among Americans. For

example, experience with Android programming

reportedly commands a premium of 20 percent in the

open market for software developers (Drapier 2011).

Matloff (2003) found skills premiums ranging from 16 to

24 percent. So, ideally statistical analyses should include a

variable for experience with “hot” skills. Yet such data are

not available for individual workers, and if, say, Android

programmers are disproportionately foreign, as the

industry claims, the analysis would misleadingly make the

foreign workers appear to be doing well relative to the

Americans. This seems to be a core problem with the Lof-

strom and Hayes study, for example.

The consequences of failing to take skill sets into account

are that (1) studies that find that H-1Bs are exploited

in wages will underestimate the degree of underpayment,

and (2) studies that find no exploitation can be mislead-

ing. In the latter case, suppose a study finds that on aver-

age H-1Bs make 5 percent more than Americans. If the

special skills for which H-1Bs are hired command a 20

percent premium on the open market, then they are being

underpaid by roughly 15 percent, all in full compliance

with the law.

In any event, the evidence supporting the finding of wage

exploitation of H-1B visa holders is consistent with what

economic theory would predict: that the H-1Bs are

underpaid relative to Americans of comparable education,

skills, and so on, due to lack of mobility. That is, if one is

not a full free agent in the labor market, which is effect-

ively the case for H-1Bs who are being sponsored for

green cards (NRC 2001; Swaim 2012b; Matloff 2003),

one will on average not get the best salary deal. Further-

more, since green cards provide highly valuable nonmon-

etary compensation, the sponsorees will generally accept

pay lower than their free market value.

The present report is not aimed at furthering the debate

on the underpayment of H-1Bs, but the issue is relevant

to our salary analyses here. For the NSCG data, this prob-

lem is solved by limiting the analysis of former foreign

students to those who are now U.S. citizens and perman-

ent residents, thus no longer exploitable. The case of the

PERM data is more complex, to be discussed later.

Target population for the NSCG collegegraduate survey data

The NSCG analysis here covers every full-time, nonma-

nagerial, nonsales worker who satisfies the following con-

ditions:

had his/her highest degree in the CS/EE field

was working full time in a U.S. position in CS/EE as

of 2003

if foreign-born, originally entered the United States

on a foreign student visa

We are thus comparing U.S. natives to former foreign stu-

dents now working in the United States. For simplicity,

this report will refer to the U.S. natives as “Americans,”

but it must be noted that many of the former students are

naturalized and are now Americans too.

In addition, for reasons explained above, in regard to the

salary analyses of NSCG data in this report, an additional

condition is imposed on the foreign-born so as to limit

the analyses to those not vulnerable to exploitation:

if foreign born, was a U.S. citizen (naturalized) or per-

manent resident as of 2003

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 7

Note also who is excluded. First, the analyses only include

those who entered the United States on a foreign student

visa—excluding those who entered on a work visa—as

explained in the methodology section above.

Also excluded are those who immigrated under family

qualifications and the like. Some researchers have found

U.S. education to be an important variable, which may

play a role in the American cultural propensity for innov-

ation. If so, then how much U.S. education is “enough”?

The easiest solution is to restrict the analyses to those

born in the United States.

As noted earlier, the analyses here effectively exclude

Indian/Indian-American outsourcing firms because these

firms import workers directly from abroad, rather than

from U.S. university campuses, the pool considered here.

And the PERM data consist almost entirely of U.S. main-

stream firms, as the outsourcing companies rarely sponsor

their workers for green cards (Hira 2010).

Wage analysis of the NSCG collegegraduate survey data

We used the following regression equation to assess how

salary is affected by age, education level, region, and ori-

ginal F-1 status:

mean wage =

β0 + β1 age + β2 age2 + β3 MS + β4 PhD + β5

highCOL + β6 origF1 +

β7 acad + β8 gov

There are control variables for age; for education, in the

form of indicator variables to code a master’s degree

(without a Ph.D.) or a doctorate (zero values for these

variables code having just a bachelor’s degree); for work-

ing in a high-cost-of-living region; for having originally

entered the United States as a foreign student; and for

working in academia or in government.

For example, the subpopulation of former foreign stu-

dents is paid on average β6 more—or less, if this quantity

is negative—than Americans of the same age, educational

attainment, and so on. A quadratic term is included for

age, as wages decline for engineers and programmers (and

other workers) after about age 50. Since the foreign work-

ers tend to work in the higher-cost-of-living areas, the

highCOL variable is important to adjust for work in such

a region, which is defined here (using NSCG’s categor-

ies) to be Mid-Atlantic, New England, or Pacific Coast.5

In addition, there are indicator variables for working in

academia and in government, to account for the generally

lower salaries in those sectors.

Table 1 presents the estimated coefficients for computer

science and electrical engineering, along with stand-

ard errors.

The estimated coefficient for the former foreign students

working in CS, -5,278, is negative and statistically signi-

ficant. In other words, they are earning significantly less

than comparable Americans. To put that numerical differ-

ence in perspective, the overall average salary is $83,296,

so the former foreign students are making about 6 percent

less than comparable Americans.6

Rather than merely reporting the results of statistical sig-

nificance tests, standard errors are also reported. Adding

and subtracting 1.96 times the standard error to the point

estimate yields a 95 percent confidence interval for the

population quantity being estimated. In this case the table

shows the point estimate and standard error to be -5,278

and 2,447, showing that we are 95 percent confident

that the former foreign students working in CS make

between $383 and $10,172 less than comparable Amer-

icans. Use of standard errors, i.e., confidence intervals,

rather than significance tests yields more informative res-

ults (Freedman, Purves, and Pisani 1998; Kaye and Freed-

man 2000).

The adjusted R-squared value was 0.119.7 This somewhat

low value, common in labor studies, reflects the fact that

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 8

T A B L E 1

Determinants of annual wages for workers in computer science and electrical engineering

Computer science Electrical engineering

Variable COEFFICIENTS (STANDARD ERROR)

Constant -18,731 -12,320

(17,759) (15,574)

Age 4,389* 3,633*

(862) (712)

Age squared -46.9* -34.2*

(10) (8)

Master’s degree 6,703* 10,338*

(2,031) (2,092)

Ph.D. 28,246* 22,671*

(4,436) (3,509)

Former foreign student (F-1) -5,278* 685

(2,447) (2,607)

High cost of living 9,543* 6,543*

(1,775) (1,830)

Academic -29,901* -18,721*

(5,097) (6,395)

Government -16,047* -1,262

(3,499) (3,133)

Adjusted R-squared 0.119 0.155

N 1327 833

* Indicates statistically significant at the 5 percent level

Source: Author’s regression analysis of National Survey of College Graduates (NSCG) data (NSF 2003)

there is great variation in individual talent levels in the

CS/EE field, even after education is accounted for. The

best software developers, for instance, have been found to

be 10 or even 20 times more productive than the weakest

ones (DeMarco and Lister 1987; Lutz 1999).

The regression results for electrical engineering (EE) are

presented in Table 1 as well. Former foreign students

working in EE earn no less but no more than U.S. natives,

as the coefficient is not significantly different from zero.

We thus see that no best and brightest trend was found for

the former foreign students in either computer science or

electrical engineering. On the contrary, in the CS case the

former foreign students appear to be somewhat less talen-

ted on average, as indicated by their lower wages, than the

Americans.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 9

Wage analysis using PERM data

The Department of Labor’s Program Electronic Review

Management data consist of records of employer-

sponsored green card applications. Each record corres-

ponds to one sponsored worker.8 The 2005–2011 data

used here9 include 32,005 applicants with software engin-

eer titles and 3,412 electrical engineers.

In the data, the employer states the wage paid and the

legal prevailing wage for the job, the latter typically

defined according to government data.10 Note that unlike

the other analyses in this paper, the workers in this dataset

are not restricted to former foreign students. In the tech

fields, the PERM workers are typically former foreign stu-

dents, but need not be.

These data are quite valuable for our goal of assessing

whether the foreign workers are typically the “best and the

brightest.” The legal prevailing wage is the average wage

for American workers in a given profession, for a given

region and a given number of years of experience. As such,

it allows us to automatically control for these variables in

assessing talent level.

If the workers are of outstanding talent, their salaries

should be much higher than average, so we have a direct

measure of talent relative to the general population of

workers in the given field, precisely our goal. In other

words, we are interested in workers with high values of

what this report will refer to as the “wage ratio” (WR), the

quotient of the wage paid to the prevailing wage.

Computing WR should in principle be ideal for our pur-

poses of identifying the prevalence of best/brightest work-

ers. But we must address the prevailing wage issue. As

noted, there are indications that the legally required pre-

vailing wage is often below true market levels, thus

enabling underpayment of H-1B workers. As previous

work has shown, one may attempt to adjust for this

(Matloff 2006). However, in the interest of simplicity, the

approach in this analysis draws on the matter from the

point of view of industry claims. The tech industry asserts

both that its foreign workers are fairly paid and that those

workers are typically “the best and the brightest.” The

research approach here is to examine whether the data are

consistent with the second claim, under the assumption

that the first one is valid.

This raises the question of the appropriate threshold for

the wage ratio to identify the best/brightest workers. The

following figures (for general populations, not foreign

workers) should provide guidance:

New Stanford CS graduates earn 37 percent more

than average CS graduates (Stanford 2010).

At 20 years after graduation, general Stanford gradu-

ates earn 28 percent more than graduates of nearby

San Jose State University (Krieger 2010).

General graduates of the most selective schools have

starting salaries 45 percent higher than graduates of

the least selective schools (Carnevale and

Strohl 2010).

These numbers correspond to WR values of 1.37, 1.28,

and 1.45. To put them in perspective, consider the 75th

percentile of wages for the occupation category “software

developer, applications,” in the Occupational Employ-

ment Statistics database.11 The ratio of 75th percentile

wage to median wage in 2011 was $111,990 / $89,280 =

1.25. Thus, a WR value of 1.28 is at roughly the 75th per-

centile. In other words, a WR of 1.28 is arguably a conser-

vative criterion for best and brightest, indicating a good

worker but not the “game changer” and “genius” workers

described earlier in this report.

Table 2 presents the share of foreign workers who satisfy

these wage criteria. It calculates the proportion of foreign

workers in software and electrical engineering whose wage

ratios are above the given thresholds.

The PERM data show that the vast majority of foreign

workers do not even meet the modest 1.28 threshold for

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 10

T A B L E 2

Share of foreign workers above ‘best and brightest’ wage thresholds, by occupation

SHARE WITH WAGE RATIO* ABOVE:

1.28 1.37 1.45

Software engineers 10.6% 6.8% 4.3%

Electrical engineers 11.1 5.3 3.2

* Wage ratio is the wage paid divided by the prevailing wage

Source: Author’s analysis of Program Electronic Review Management (PERM) data (U.S. DOL 2005–2011)

T A B L E 3

Share of foreign workers above ‘best and brightest’ wage thresholds, by firm

SHARE WITH WAGE RATIO* ABOVE:

1.28 1.37 1.45

Cisco 10.7% 7.2% 4.8%

eBay 24 19.9 18.3

Hewlett-Packard 24.9 18.9 12.2

Intel 24.3 17.6 14.5

Google 27.8 18.3 12.3

Microsoft 25.9 13.9 7.9

Motorola 5 3.2 2.6

Oracle 37.7 29.8 25.6

Qualcomm 2.5 1.2 0.1

* Wage ratio is the wage paid divided by the prevailing wage

Source: Author’s analysis of Program Electronic Review Management (PERM) data (U.S. DOL 2005–2011)

best and brightest, let alone the more stringent defini-

tions.

Recall that this dataset consists of workers at mainstream

U.S. firms, not Indian outsourcing companies. It is

instructive to look at specific firms. Table 3 presents the

distribution of foreign workers’ wage ratios at the largest

tech users of the green card system. It shows that in some

firms there are more foreign workers above the various

thresholds to qualify for best and brightest than for the

labor market as a whole, as shown in Table 2. However,

for every firm listed in Table 3, the solid majority of

their foreign software and electrical engineers do not meet

even the mildest of the three thresholds for best/brightest,

1.28, or roughly the 75th percentile of wages in the gen-

eral market.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 11

A look at the Microsoft salary data

Bill Gates has stated that Microsoft pays its foreign work-

ers “$100,000 a year to start” (Broder 2006). Bill Kamela

of the Microsoft Policy Council has made a similar claim

regarding Microsoft starting salaries for software engineers

(Kamela 2012). Yet these claims are not confirmed at all

by the PERM data.

The data show that only 21 percent of the workers

Microsoft sponsored for green cards during 2006–2011

had salaries of at least $100,000. In fact, only 18 percent

of Microsoft’s sponsored workers with software engineer-

ing titles were above the $100,000 mark. If salary level

is indicative of the best and the brightest, as Gates and

Kamela suggest, only a minority of Microsoft’s foreign

hires would qualify.

By contrast, 34 percent of Microsoft’s green card

sponsorees with financial analyst titles made over

$100,000, as did 71 percent of its lawyers in the PERM

data. It would seem that, counter to its rhetoric, engineers

are not top priority for Microsoft, a point to be discussed

again later in this report.

Salary and English-language ability

Finding that Asian immigrants lagged behind comparable

Europeans in salary, Hunt (2011) speculated that the

cause was poor English skills among the Asians. This

raises the question of whether the modest WR values

seen above are artificially low, due to language. However,

Hunt’s speculation does not seem to be borne out in the

case of CS/EE.

The tech industry is famously meritocratic for nonman-

agement engineering workers. Since workers produce tan-

gible products of direct, crucial value to the firms, all

that matters to their employer is whether they successfully

wrote the code or designed the chips; if they did, they are

rewarded, even if their grammar is flawed.

Professor Joyce Tang found that language skills were not

a barrier to Asian immigrant engineers relative to the

Caucasian immigrants, even for those who wished to

obtain academic positions (Tang 2000). A logistic regres-

sion analysis performed by the author on the Census’s

2000 Public Use Microdata Sample (PUMS) (not presen-

ted here) shows that, among immigrant Chinese engineers

and programmers, English skill had no statistically signi-

ficant impact on the probability of earning a high salary,

defined to be above $150,000.

Moreover, in viewing Hunt’s analysis of the workers from

Asia, it must be noted that Indians are by far the numer-

ically dominant H-1B nationality group in the tech area,

and Indian students typically grow up speaking English.12

Dissertation awards amongforeign and U.S. students

The previous sections analyzed wages, presuming that the

top innovators in a firm would also get top wages. This

and some succeeding sections more directly address the

innovation and quality issues. In this section, we examine

awards for top Ph.D. dissertations. Such an analysis exam-

ines only a small sliver of graduate accomplishments but

nevertheless provides some useful information.

Each year, the Association for Computing Machinery

(ACM) selects one or more dissertations in computer sci-

ence for its ACM Doctoral Dissertation Awards. These

awards by definition select the very top innovator or

innovators. The ACM’s press release for its 2010 award,

for instance, stated:

Craig Gentry has won the 2009 Doctoral Disser-

tation Award from ACM…for his breakthrough

scheme that solves a central problem in crypto-

graphy. …His dissertation…adds a crucial layer of

safety and privacy to the online world in settings

ranging from banking and healthcare to networks

and cloud computing. This approach allows users

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 12

to outsource the processing of data without giving

away access to the data. …(ACM 2010)

The dissertation awards data enable a direct examination

of the innovative talent of foreign students.13 By com-

paring the percentage of foreign students among the

awardees to the percentage of foreign students among

all doctorates earned in computer science, we can assess

whether foreign students disproportionately win

the award.

The NSCG data show that 51 percent of the computer

science Ph.D.s in the United States as of 2003 had ori-

ginally entered the United States as foreign students. The

Computing Research Association’s annual Taulbee Survey

shows that, of the CS Ph.D.s granted between 1994 and

2007 (mainly in the United States, but including Canada

as well), 48 percent went to international students.

When the ACM first started its dissertation awards pro-

gram in 1978, there were fewer Chinese foreign stu-

dents—an important group, thus those earlier years are

not included. Instead, 1985 was used as the starting point,

following the lead of Orleans, who viewed the influx of

Chinese foreign students as having hit a steady level by

then (Orleans 1988).14

During the period 1985–2009, 29 dissertation awards

were given to students at North American universities (28

in the United States, one in Canada). Of these, 14 went

to foreign students. This fraction, 0.48, has a margin of

error of 0.19, and is not statistically different from the fig-

ures of 0.51 and 0.48 stated above for the proportion for

former foreign students among CS Ph.D.s.

Thus, foreign students earned the dissertation award

roughly in proportion to their presence in the doctoral

student population, again indicating that the foreign stu-

dents are similar to, rather than more talented than, their

American classmates.

Quality of institution ofdoctoral study

If the “best and brightest” image projected by the industry

for STEM foreign students were accurate, it should be

reflected in a tendency for the students to be enrolled

in the more highly ranked U.S. institutions. However,

Bound, Turner, and Walsh (2009) found the opposite to

be the case:

In physics, biochemistry, and chemistry much of

the expansion [from the mid-1980s to mid-90s]

in doctorate receipt to foreign students occurs at

unranked programs or those ranked outside the

top 50; the growth in foreign students in engin-

eering is distributed more evenly among pro-

grams. Among students from China, Taiwan, and

South Korea growth has been particularly concen-

trated outside the most highly ranked institutions.

With this in mind, we performed a similar, more thor-

ough analysis for computer science students for

this report.

In a 2010 study, the National Research Council assessed

the quality of Ph.D. programs in most major fields and

at most major universities (NRC 2010). This survey

includes data on the percentage of international students

in a given program at a given school, a figure which allows

an assessment of the quality of schools attended by for-

eign students.

Though the NRC rated each program, its method was

imputational—it developed a statistical formula to serve

as a proxy for reputation—and its ratings sparked contro-

versy (Aaronson 2010). This report uses the U.S. News

and World Report ratings of computer science Ph.D. pro-

grams, which “are based solely on the results of surveys

sent to academics….” (Morse 2012). USNWR assigns rat-

ings from 1.0 to 5.0, but did not publish those falling

below 2.0. (The data used cover the top 128 schools.) The

data are for the period 2001–2006.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 13

T A B L E 4

Quality of U.S. schools attended by foreign and U.S. computer science students

A. Program rating Average program rating

Foreign 3.44

American 3.71

B. Top/bottom programs Share of foreign students

Top 10 programs 45.7%

Bottom 10 programs 66.5

C. Share in top schools Share from top 10 schools

American 26.6%

Foreign 16.8

Source: Author’s analysis of National Research Council (2010)

Table 4 presents tabulations of the NRC data on the qual-

ity of schools attended by foreign computer science stu-

dents. Panel A shows the mean program quality ratings

for the foreign and American students. The results suggest

that Americans attend more selective, higher-quality uni-

versities than do foreign students when earning Ph.D.s in

computer science.

Panel B in Table 4 provides data on the share of foreign

students among the 10 strongest and weakest university

programs. These figures are consistent with the Bound

study, i.e., there are higher percentages of foreign students

in the weaker computer science programs.

Panel C of Table 4 shows the percentages of American and

foreign students who come from the top-10 CS programs.

Americans are more likely to earn their computer science

Ph.D.s in a top school than are foreign students (26.6 per-

cent of American students vs. 16.8 percent of foreign stu-

dents).

The quality of a degree program, and in particular the

selectivity of admissions to that program, does not fully

reflect the quality of individual students. A low-ranked

school will generally have a few truly outstanding stu-

dents, and the selectivity of a highly ranked program may

not be as keen as the ranking would imply.15

Nevertheless, a program’s ranking is a fairly good measure

of the average quality of the students from that program.

Thus, the data above indicate that the foreign students

generally are not more talented or better educated than

the Americans; on the contrary, the foreign computer

science Ph.D. students attend weaker-than-average pro-

grams.

It would be of interest to perform similar analyses at the

master’s degree level. Unfortunately, there do not seem

to be such data available, tabulated by school and field.

Anecdotally though, it appears that enrollments in CS

master’s programs at the non-Ph.D. granting schools are

even more heavily weighted toward foreign students than

at the Ph.D. level. In the case of California State

University, East Bay,16 for example, 90 percent of the CS

master’s students are international (Jaschik 2012).

Patents awarded to American andforeign workers

Several recent studies on immigrant patenting in the tech

area have attracted considerable attention (Wadhwa et al.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 14

2007; Hunt 2010; Kerr 2010). However, they are not very

useful in the present context, as their findings essentially

boil down to the conclusion that immigrants are numer-

ous in the tech field, and thus they are also numerous in

patent activities.17

None of these studies addresses the central question rel-

evant here, which is whether the foreign worker programs

are raising our average level of tech talent. Are the immig-

rant tech workers more prone to patenting on a per capita

basis, after education and other variables are taken into

account? If the United States is indeed facing an internal

brain drain, the critical question is: Are the immigrants of

higher quality than those they are displacing?

Hunt’s second study (Hunt 2009 is the working paper

version; Hunt 2011 the final) addressed this question. In

the working paper, she wrote, “After I control for field of

study…and education…both main work visa groups and

student/trainee visa holders have statistically significantly

lower patenting probabilities than natives.” In the final

published version the dataset coverage was somewhat dif-

ferent, but she still found no statistically significant differ-

ence between immigrants and natives.

As mentioned, though, Hunt cast a broad net in her work,

encompassing myriad fields and types of entry visas, in

contrast to the narrower focus of the research presented

here on former foreign students in computer science and

electrical engineering.

Let us turn again to analysis of CS/EE in the NSCG

data. Unlike the earlier analysis, we no longer restrict

the sample to U.S. citizens and permanent residents. The

sample does exclude those in academia and government,

where patenting rates are lower. Table 5 presents regres-

sion analyses of patent applications, overall and commer-

cialized, for computer science (columns 1 and 2) and elec-

trical engineering (columns 3 and 4). In each case there

are controls for level of education (dummy variables for

either master’s degree or Ph.D.) and age, and whether the

worker is a former foreign student (original F-1 status).

In column 1, the coefficient for computer science workers

who were former foreign students, -0.439, is significantly

different from zero at the 5 percent level. In other words,

among computer science workers, on average, the former

foreign students are producing about half a patent applic-

ation fewer per person than are Americans of the same age

and education level.

On the other hand, in electrical engineering (column 3),

the former foreign students’ patenting activity is not sig-

nificantly different from the Americans.

The NSCG data also tally commercialized patents, so

Table 5 presents analyses of the propensity to procure

commercialized patents by computer science (column 2)

and electrical engineering (column 4) workers. The results

are similar to those for all patents. Former foreign stu-

dents in computer science produce 0.118 fewer commer-

cialized patents than their American counterparts of the

same age and education level. On the other hand, former

foreign students in electrical engineering produce a com-

parable number of commercialized patents to their Amer-

ican counterparts.

In summary, the former computer science students apply

for somewhat fewer patents than do their American peers,

and also are awarded fewer patents that are eventually

commercialized. In the case of electrical engineering, the

foreign and American groups have the same mean num-

bers of patent applications, both general and commercial-

ized.

Again, the data do not show a best and brightest tendency

among the former foreign students.

Rates of working in R&D

Presumably much (though by no means all) of the innov-

ation in the tech industry comes from those working in

research and development positions. It is thus of interest

to investigate the proportions of U.S. versus immigrant

workers who hold such jobs. Fortunately, the NSCG data

include a variable for this status.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 15

T A B L E 5

Determinants of patent application rates, overall and commerical

COMPUTER SCIENCE ELECTRICAL ENGINEERING

Allpatents

Commercializedpatents

Allpatents

Commercializedpatents

Variable (1) (2) (3) (4)

COEFFICIENTS (STANDARD ERROR)

Constant 0.185 -0.113 0.571 0.008

0.298 0.084 0.455 0.162

Age 0.002 0.005* 0.002 0.004

0.007 0.002 0.010 0.004

Master’s degree 0.442* 0.107* 0.201 0.143

0.141 0.039 0.236 0.084

Ph.D. 2.90* 0.226* 2.98* 0.351*

0.305 0.085 0.382 0.136

Former foreign student(F-1) -0.439* -0.118* -0.045 -0.052

0.162 0.046 0.280 0.100

Adjusted R-squared 0.066 0.014 0.083 0.007

N 1248 1248 766 766

* Indicates statistically significant at the 5 percent level.

Source: Author’s regression analysis of National Survey of College Graduates (NSCG) data (NSF 2003)

Since the outcome is binary (you either work in R&D

or you do not), a logistic (“logit”) regression model was

used rather than a linear one. A logit regression still forms

a weighted sum of the predictor variables as in linear

regression, but it models a probability instead of a general

mean, in this case the probability of working in R&D.

The results of the logit model for both computer science

and electrical engineering, looking at the probability of

working in R&D while controlling for age (and the

square of age18) and education level, are presented in

Table 6. The estimated coefficients from a logit regression

are interpreted as the rate of change in the “log odds”

of (in our case) working in R&D, as the independent

variables change. As is common practice in discussions of

logit regression results, here we discuss the more intuit-

ive “marginal effect” of being a foreign former student for

specific values of the other independent variables.

The data indicate that in both computer science and elec-

trical engineering, the foreign former students are signific-

antly less likely to work in R&D, compared to Americans

of the same age and educational background.

For example, consider 30-year-old workers with master’s

degrees. In computer science, substitution into the logit

formula shows that the Americans are about 10 percent

more likely to be working in R&D than are comparable

foreign former students (a 0.89 probability versus 0.81).

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 16

T A B L E 6

Determinants of rates of R&D work

Variable Computer science Electrical engineering

COEFFICIENTS (STANDARD ERROR)

Constant 1.03 8.14*

1.36 3.06

Age 0.02 -0.27

0.07 0.14

Age squared 0 0

0.00 0.00

Master’s degree 0.46* 1.14*

0.17 0.40

Ph.D. 2.32* 2.17*

0.62 0.79

Former foreign student (F-1) -0.66* -1.36*

0.19 0.38

N 1253 771

* Indicates statistically significant at the 5 percent level

Source: Author’s regression analysis of National Survey of College Graduates (NSCG) data (NSF 2003)

In electrical engineering, the difference is dramatic—the

Americans are 68 percent more likely to be in R&D than

the foreign former students, with the probability of R&D

work being 0.76 for the Americans but only 0.46 for the

foreign former students.

These are interesting results. One might take the view that

considering patents or dissertation awards is setting the

bar too high: A worker might be quite innovative without

necessarily having the work patented, and the bar for the

dissertation awards is extremely high. These latter find-

ings, however, address the industry’s core source of innov-

ative work, its R&D units, and the data show that these

units are staffed disproportionately by Americans rather

than by foreign former students.

Summary of thestatistical analyses

In addressing any question such as this one regarding the

relative skills and talents of groups of workers, it is desir-

able to consider a variety of approaches and multiple data-

sets. In the end, one should consider the “preponderance

of the evidence,” the overall trend in the various analyses.

The research presented here analyzed four separate data-

sets on five different variables, with consistent results:

The immigrant workers, especially those who first

came to the United States as foreign students, are in

general of no higher talent than the Americans, as

measured by salary, patent filings, dissertation awards,

and quality of academic program. In the computer

science case, the former foreign students are in fact

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 17

generally of significantly lower talent in many aspects

than Americans of the same age, education, and

so on.

The immigrant workers who first came to the United

States as foreign students are significantly less likely

than Americans to be working in R&D, the industry’s

main source of innovation. This is true for both com-

puter science and electrical engineering.

Is there a tech labor shortage?

If the foreign workers are not being hired generally

because they are the best and the brightest, are they being

used to remedy labor shortages? The topic is addressed in

this section.

When the tech industry lobbied Congress to raise the

yearly H-1B cap in 1998, the industry claimed a major

STEM labor shortage, and it has continued to make such

claims in the years since. Yet no study, other than those

sponsored by the industry, has ever confirmed a shortage.

(See Matloff (2003) for a compilation of the various stud-

ies conducted in the first several years following 1998.)

More recent data also counterindicates shortage claims.

The National Association of Colleges and Employers

(NACE) tracks salaries of new graduates. NACE reports

that computer science starting salaries just kept pace with

inflation from 2010 to 2011, with a 1 percent increase

(NACE 2011). Though electrical engineering was an

exception, with a 4.4 percent advance (after a dip of 1.2

percent the previous year), overall engineering starting

salaries essentially stayed flat since 2010, with a 0.3 per-

cent increase. And the 2010 salary levels were actually 0.5

percent lower than in 2009 (NACE 2011).

The trend has been similar for experienced workers. For

example, the Internet job board Dice.com found that, at

least among job openings posted on its site, IT wages

rose less than 1 percent from 2009 to 2010 (Dice 2011).

Wages for software engineers reportedly rose just 2.5 per-

cent from October 2011 to October 2012 (Samson

2012). Costa (2012) found that wages in computer and

mathematical occupations are increasing only 0.5 percent

per year.19

One of the industry’s most effective public relations tacks

has been to claim that too few Americans major in STEM

fields in college. This claim has been refuted by the

45-page Urban Institute study (Salzman and Lowell

2007) for STEM in general, and in the engineering case

by semiconductor giant Texas Instruments (2011). The

company’s vice president for worldwide human resources,

Darla Whitaker, testified that the firm had no shortage of

American engineering applicants at the bachelor’s degree

level. (Graduate degrees are discussed later in this report.)

The internal brain drain(‘diversion’)

A term currently popular in STEM policymaker circles

is diversion, referring to workers with a bachelor’s degree

or higher in STEM but who work in non-STEM fields

(Bernstein, Lowell, and Martin 2011; Carnevale, Smith,

and Melton 2011). Though this is a recognition of the

fact that there is indeed an internal brain drain occurring

in STEM, it does not address the questions of why this is

occurring. The issue is addressed in this section, and the

nexus of this internal brain drain with the H-1B and other

foreign worker programs will be shown.

On July 7, 2012, the Washington Post (Vastag 2012)

reported on a major study by a high-level committee in

the National Institutes of Health (NIH). The main find-

ings were that the vast majority of those with doctor-

ates in the life sciences are never able to secure a research

job in the field, even after years of low-paid postdoctoral

research work. The article illustrated the point with per-

sonal cases, such as a woman with a doctorate in neuros-

cience now working as an administrative assistant.

Readers who followed up by watching the video present-

ation of the NIH report (NIH 2012) may have been

startled to find that the H-1B visa is part of the over-

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 18

supply problem; the video mentioned the role of foreign

researchers in the United States at several points. Approx-

imately 54 percent of postdoctoral researchers are foreign,

most of them on H-1B visas (Davis 2006). The NIH

committee also stated that the resulting huge labor sur-

plus, and the ensuing low wages and poor career pro-

spects, are driving many of the nation’s best and brightest

out of the field.

The diversion of educated workers due to the foreign

influx is not at all limited to the lab sciences. A team of

Berkeley economists identified this same problem in the

CS/EE context in 1998 and elaborated on the point in a

2009 book (Brown and Linden 2009):

…high-tech engineers and managers have experi-

enced lower wage growth than their counterparts

nationally. …Why hasn’t the growth of high-tech

wages kept up? …Foreign students are an important

part of the story. …Approximately one-half of

engineering Ph.D.s and one-third of engineering

MSs were granted to foreign-born students in the

mid-1990s. (Brown, Campbell, and Pinsonneault

1998, emphasis added)

The H-1B-caused internal brain drain was actually anti-

cipated, if not actually planned, in the government’s cent-

ral science agency back in 1989. The Policy Research and

Analysis (PRA) division of the National Science Founda-

tion (NSF) complained that Ph.D. salaries were too high.

In an unpublished report, PRA proposed a remedy in

the form of importing a large number of foreign stu-

dents, stating:

These salary data show that real Ph.D.-level pay

began to rise after 1982, moving from $52,000 to

$64,000 in 1987 (measured in 1984 dollars). One

set of salary projections show that real pay will

reach $75,000 in 1996 and approach $100,000

shortly beyond the year 2000. …

[To] the extent that increases in foreign student

enrollments in doctoral programs decline or turn

negative for reasons other than state or national

policies it may be in the national interest to act-

ively encourage foreign students. …

A growing influx of foreign Ph.D.s into U.S. labor

markets will hold down the level of Ph.D. salaries.

…[The Americans] will select alternative career

paths…by choosing to acquire a “professional”

degree in business or law, or by switching into

management as rapidly as possible after gaining

employment in private industry…[as] the effective

premium for acquiring a Ph.D. may actually be neg-

ative. (Weinstein 1998; emphasis added)

It is not clear whether the PRA report represented official

NSF policy. However, the report did correctly project that

the H-1B and related programs would drive American

students away from doctoral study, i.e., would cause an

internal brain drain in STEM.

Significantly, the PRA accurately forecast that the STEM

wage suppression would cause American students to shift

to business and law. As seen earlier, the PERM data show

that Microsoft pays its financial analysts and lawyers

much more than it pays its engineers.

Former Federal Reserve chairman Alan Greenspan has

made a number of public statements advocating the

importation of foreign tech workers as a means of holding

down salaries (Thibodeau 2009). (Greenspan referred to

tech workers as a “privileged elite,” apparently not placing

the much higher-paid professions in the legal field and

on Wall Street in that category.) The congressionally com-

missioned National Research Council study also con-

cluded that H-1B adversely impacts tech wages (NRC

2001, 187).

Note that diversion cannot be viewed as a failure of the

American K-12 educational system, as is often claimed.

True, some students are weak in STEM or are disinter-

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 19

ested in it, but the points made above apply to students

who are skilled at STEM, and who do specialize in STEM

in college. As remarked above, the issue of diversion con-

cerns workers who have bachelor’s degrees in STEM but

who, either immediately after attaining their degrees or

later on, are working outside of STEM. Indeed, in the

NIH study discussed above, the workers have doctorates

in STEM, plus years of postdoctoral work.

As noted, the NIH fretted that the H-1B visa is resulting

in loss of career to many Americans in lab science. In

addition, the stagnant salaries caused by the foreign influx

discourage young people from pursuing a career in

STEM. Young people see these market signals and

respond accordingly. Even many Indian immigrant engin-

eers’ children see the tech field as unstable, subject to

outsourcing to India (Grimes 2005). The talents STEM

students have been applying—keen quantitative insight,

good problem-solving and analytical skills, and so

on—are much more highly rewarded outside STEM, as

exemplified by the Microsoft salary analysis above. Geor-

getown University researcher Anthony Carnevale has

remarked, “If you’re a high math student in America,

from a purely economic point of view, it’s crazy to go into

STEM” (Light and Silverman 2011).

A Forbes Magazine article cites the troubling effects of

stagnant salaries and offshoring:

Between 2003 and 2006 the percentage of gradu-

ates from MIT going into financial services rose

from 13 percent to almost 25 percent. …One can

hardly blame these young hires. Financial firms

offer considerably higher pay, better career pro-

spects and insulation against off-shoring, than tra-

ditional science and engineering companies. …

(Schramm 2011)

Gavin (2005) summarized the connection made by

Richard Freeman of Harvard:

In his paper, Freeman argues that fewer American-

born workers pursue science and engineering not

only because they have more career choices than

foreign workers, but also because some choices

offer better wages. Average annual salaries for law-

yers, for example, amounted to more than

$20,000 above those for doctoral-level engineers

and $50,000 more than those for life scientists

with doctorates, according to Census data that

Freeman cites in the paper….

U.S. companies, he added in an interview, have

been quite willing to encourage a foreign supply

of technical workers. This has allowed them to

pay lower wages, but it has also created conditions

that make science and engineering less attractive

to Americans.

“You can’t say, ‘I want more visas’ and ‘I expect

more Americans to enter the field,’” Freeman said.

“The thing that always strikes me about these

business guys is they never say, ‘We should be pay-

ing higher salaries.’”20

This internal brain drain might have been justified if the

foreign workers were of higher caliber than the Americ-

ans, but, as shown earlier, this is not the case. The consist-

ent theme in the results here has been that the immigrant

engineers and programmers who first come to the United

States on student visas—the group the industry lobbyists

claim are most talented—are quite similar to the Amer-

icans in talent, or are of lesser talent than the Americans,

contrary to the “genius” image projected by the industry.

Green card indenture

A little-discussed but vital aspect of the current green card

sponsorship process is that it effectively ties the foreign

worker to the employer for a number of years. This con-

dition allows for the legal exploitation of foreign workers

but also has negative consequences for American workers,

since they become less attractive to employers than the

exploitable foreign workers.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 20

If you are a Silicon Valley employer in the midst of an

urgent project, you suffer a major loss if an engineer

suddenly leaves for another employer. Hiring a foreign

worker and sponsoring him for a green card remedies

your predicament, as the worker becomes a de facto inden-

tured servant (NRC 2001). Such exploitation is pitched

by immigration attorneys to employers as the major

attraction of green card sponsorship. For example, lawyer

David Swaim, whose online biography notes that he “cre-

ated the immigration procedures at dozens of companies

such as Texas Instruments…” (Swaim 2012a), advises

employers that the captive nature of green card sponsorees

is a huge win for the employer:

By far the most important advantage of [green

card sponsorship] is the fact that the employee is

tied to a particular position with one company

and must remain with the company in most cases

for more than four years. … (Swaim 2012b)

That immobility is extremely valuable to the employer in

the sense of preventing worker losses during projects, and

it can tie in to the wage issue as well. FACEIntel, an Intel

dissident worker group, has reported that an Intel human

resources representative “…told staff of the Micropro-

cessor Technology (MT) group, ‘…after hiring the for-

eign student, delay the immigration paper work process,

because once they get their green cards we lose them

to companies like Sun Microsystems and Silicon Graph-

ics, they pay them about 30 percent more’” (FACEIn-

tel 1996).

The point relevant here is that this indenture, in Swaim’s

words, is “the most important advantage” to employers

of green card sponsorship, and puts American job applic-

ants at a substantial disadvantage. The employer has a big

incentive to hire a foreign worker in lieu of a similarly

qualified American.

H-1B and age discrimination

H-1B also has a major impact on “older” workers—which

in the realm of H-1B and the tech field can mean anyone

over age 35. Employers prefer to hire younger, thus

cheaper, H-1Bs instead of older, thus more expensive,

Americans. The NSCG data show a wide difference in

ages, with a mode of age 29 for the H-1Bs in CS/EE

versus 42 for the Americans.

The tech industry’s hiring focus on the young has been

well documented (NRC 2001; Brown, Campbell, and

Pinsonneault 1998; Brown and Linden 2009). Microsoft

admits that “the vast majority of Microsoft hires are

young, but that is because older workers tend to go into

more senior jobs and there are fewer of those positions to

begin with” (Wadhwa 2008; emphasis added).

The industry claims that older Americans can’t be hired

because they lack up-to-date skills and need retraining.

But this assertion is at odds, for example, with the doc-

umented incidents in which major U.S. firms have fired

American workers and forced them to train their foreign

replacements (Hira 2010); in these situations, clearly it

was the Americans who had the skills, not the foreign

workers. Instead, the skills issue is a pretext for hiring

cheaper workers. Former tech CEO (and current sup-

porter of foreign tech visas) Vivek Wadhwa has spoken on

this a number of times, saying, for example:

…even if the [older] $120,000 programmer gets

the right skills, companies would rather hire the

younger workers [at $45,000]. That’s really what’s

behind this. (Lehrer 2009)21

In summary, the foreign worker programs are causing an

internal brain drain in the United States, in which the

nation’s own best and brightest are either displaced or dis-

couraged from entering the tech field in the first place.

What should be done

We refer to the following two points as axioms, rather

than merely as goals, to emphasize the reasonable assump-

tion that everyone on either side of the high-skilled

immigration debate supports them:

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 21

Axiom I: The immigration to the United States of the

world’s genuinely best and brightest in science, techno-

logy, engineering, and math (STEM) should be encour-

aged and facilitated.

Axiom II: U.S. immigration policies should not discour-

age America’s own most talented young people from pur-

suing a STEM career.

The discussion above on the internal brain drain, partic-

ularly the statements by analysts at the premier govern-

ment science agencies NIH and NSF, demonstrates that

current immigration policy is antithetical to Axiom II.

The present policy is causing an internal brain drain from

STEM careers.

Furthermore, the findings and remarks coming out of

NIH and NSF imply that what should not be done is

grant automatic green cards to foreign STEM students

studying at U.S. universities, as has been proposed. Flood-

ing the labor market would worsen the problems, not

solve them.

Indeed, the NSF Policy Research and Analysis document

points out a market flood would flow from a policy that

automatically grants green cards. The NSF report makes

this proposal:

…Another approach [to ensuring a large influx

of foreign students] is to grant permanent resident

status or immigrant status to foreign students suc-

cessfully completing Ph.D. degrees at U.S. Institu-

tions. (Weinstein 1998; emphasis added)

If we accept the NSF internal report’s point, cited in the

last section, that bringing in more foreign students would

drive away American students, then its support for an

automatic green card program is counter to Axiom II, i.e.,

it would discourage U.S. students from pursuing STEM.

This is a strong argument against the current green card

proposals.

As discussed earlier, foreign worker programs allow

employers to avoid hiring older Americans. Proposed

legislation granting automatic green cards to new foreign

graduates would have the same adverse impact as the

H-1B program currently does, since the beneficiaries

would mostly be young. Again, this possibility argues

against automatic green card proposals.

And in light of the tech industry’s (debunked) claim that

the reason it does not hire older workers is that the rapidly

evolving technology has passed them by, what would be

the point of granting automatic green cards to foreign

STEM students? In a few years, the technology will have

passed them by too. They will have permanent residency

but obsolete skills.

Thus, proposals for automatic granting of green cards

to STEM foreign students would be unwarranted and

indeed harmful.

What, then, is the proper way to accomplish the goals in

Axioms I and II? Consider first Axiom I. How can we

facilitate the immigration of individuals who are genu-

inely the best and brightest?

The employment-based green card quotas should be

rebalanced to provide a greater share of the visas to

the categories that the current statute gives to “the

best and the brightest,” i.e., the first employment-

based green card category (EB-1, for “foreign nation-

als of extraordinary ability” and “outstanding profess-

ors”), as well as the second (EB-2, for those with

“exceptional ability” or “[possessing] an advanced

degree”). EB-1 visas are processed relatively quickly,

with no wait for a quota slot in most years, but some

of the quota in the third category (EB-3, for those

“[possessing] a bachelor’s degree”) should be shifted

to EB-2.

The wage ratio (WR) analysis in this report suggests

an alternative to the automatic green card proposals,

one directly targeted to bringing in outstanding tal-

ents, the industry’s professed goal. Instead of granting

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 22

automatic green cards to a broad class of foreign

STEM students, such a program could be limited to

any worker having a legitimate job offer with a WR

value above a certain threshold in STEM occupa-

tions. The 90th percentile corresponds to a WR value

of about 1.53 for software engineers, for example, so

this might serve as a starting point for the discussion.

The existing O-1 temporary work visa22 and the

National Interest Waiver in the EB-2 green card cat-

egory are both aimed at the best/brightest group, but

some argue that the criteria in these visas are too strin-

gent. This might be revisited.

Concerning Axiom II, we need to assure that programs

like H-1B are used only to attract the best and the bright-

est or to remedy genuine labor shortages—not to serve as

a source of cheap, compliant labor. The employer incent-

ives for using foreign workers as cheap labor must be

removed, and the practice of using green card sponsorship

to render the foreign workers captive must be discontin-

ued.

The first task in removing the cheap-labor incentive is

to reform the legal definition of prevailing wage, which

is riddled with loopholes that permit the underpayment

of H-1B workers relative to their true market value. The

redefinition of prevailing wage in the H-1B reform legis-

lation introduced by Senators Richard Durbin (D-Ill.)

and Charles Grassley (R-Iowa) defines the prevailing wage

as the median wage in the occupation and local

area—without breaking the wage down by experience

level. This would be a major step forward.

Also, currently the statute defines the prevailing wage in

terms of the job, not the worker. This enables an employer

to, for example, hire a foreign worker with a master’s

degree at the price of a bachelor’s degree holder. This must

be fixed too, perhaps by setting a separate prevailing wage

scale for holders of postgraduate degrees. Otherwise, the

value of a master’s degree for U.S. workers will be dimin-

ished, exacerbating the internal brain drain.

Regarding green card sponsorship, again the definition of

prevailing wage must be reformed, in the manner dis-

cussed for the H-1B visa above.

Loopholes in green card law

Legal loopholes involving the definition of what consti-

tutes a “qualified” worker for purposes of permanent labor

certification must be closed. The laws should not force an

employer to hire an American who cannot perform the

job well, but it is commonplace for employers to narrowly

tailor job requirements so that only the desired foreign

applicant qualifies. This and other loopholes were illus-

trated dramatically in a YouTube video series produced by

a Pittsburgh immigration law firm, Cohen and Grigsby

(Weier 2007). There a partner emphasized:

And our goal is, clearly, not to find a qualified and

interested U.S. worker. And you know in a sense

that sounds funny, but it’s what we’re trying to do

here. We are complying with the law fully, but our

objective is to get this person a green card….

Cohen and Grigsby is not a rogue business; it is one of

the most prominent law firms in the Pittsburgh area, and

often quoted in the press. The partner who made the

remark is an adjunct professor at the University of Pitts-

burgh. In other words, the firm’s behavior here is stand-

ard practice in the field, and was in fact defended by

the American Immigration Lawyers Association spokes-

person (Sostek 2007). Joel Stewart, one of the nation’s

most prominent immigration lawyers, has said, “Employ-

ers who favor aliens have an arsenal of legal means to

reject all U.S. workers who apply” (Stewart 2000).

Abuse of foreign worker programs is thoroughly main-

stream, both in terms of employers and in terms of the

prestigious immigration law firms involved.23 Focusing

exclusively on Indian outsourcing firms while ignoring

the mainstream firms that abuse the visa program would

be unwarranted scapegoating. And imposing special

restrictions on Indian firms’ use of H-1B visas should

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 23

not be allowed to serve as cover for failing to tackle the

broader problems in the H-1B visa program.

—Dr. Norman Matloff is a professor of computer science

at the University of California, Davis. His commentary and

analyses of high-skilled immigration issues have appeared in

various academic journals and media outlets, and he has

written extensively on the subject. Dr. Matloff received his

Ph.D. in mathematics from the University of California, Los

Angeles.

Endnotes1. This is seen in the annual Report on Characteristics of

Specialty Occupation Workers (H-1B) from the U.S.

Customs and Immigration Service (USCIS). For fiscal year

2001, for instance, CS had 52.1 percent of the total, and the

next-largest category, EE, had 4.7 percent.

2. These firms, colloquially referred to as “bodyshops,” rent

programmers, almost all of whom are foreign workers, to

other U.S. firms.

3. The author performed an analysis on research paper counts

and found no difference between the immigrant and U.S.

tech workers, but it is not presented here.

4. The publication Hunt (2009) is a working paper, and its

analysis included those currently on a work visa. This group

was not included in the final published paper, Hunt (2011).

5. Unfortunately, the dataset does not have a finer description

of region. The hiCOL variable does not include the major

high-tech area of Chicago, for example. This results in some

residual overstatement of the wages of the former

foreign students.

6. Many labor analyses regress the logarithm of wage, rather

than the wage itself. However, this produces distortion if the

original relationship was not exponential.

7. The adjusted R-squared value is similar to the familiar

R-squared fit measure, but modified to account for possible

overfitting.

8. The PERM data should not be confused with the Labor

Condition Application (LCA) data associated with the H-1B

visa. An LCA record does not necessarily correspond to an

actual worker.

9. Data are also available for the period 2000–2004. However,

a rule change occurred starting with the 2005 data

(previously it was permissible to pay as much as 5 percent

below prevailing wage), so the analysis here is restricted to

that period. Another point to mention is that beginning in

2005, employers have had the option of stating offered salary

as a range rather than an exact figure. Records with salary

ranges are excluded here, thus eliminating around 10 percent

of the records each year. WR, the statistic computed here,

appears not to have been affected by this exclusion, as

evidenced by comparing pre- and post-2005 medians.

10. For the year 2005, for example, 91 percent of the

applications based their prevailing wage values on the OES

database compiled by the Bureau of Labor Statistics. In some

cases the employer uses a private survey, yielding a level

preferable to the employer (i.e., a lower level).

11. The government figures for prevailing wage are based on

the OES data. The numbers cited here are from

http://www.bls.gov/oes/current/oes1511232.htm.

12. Hunt herself, in a more recent paper that investigates the

language issue more directly, also finds that language has

little impact on nonmanagement tech workers (Hunt 2012).

13. Information gleaned from the Web, such as CVs,

biographies, and so on, was used to determine whether the

awardees were international students. If for instance a

student had done undergraduate work abroad, then he was

counted as a foreign student at the time he won the Ph.D.

award at a U.S. school.

14. The students started coming to the United States after

China opened in 1979. The numbers were small at first, but

as a CS professor handling graduate admissions at the time, I

found that the influx was strong by the mid-1980s, jibing

with the Orleans figure.

15. Many of the top CS programs bring in large amounts of

research grant funding, and thus need large numbers of

research assistants. Anecdotally, I have found that this

pressing need sometimes results in some compromise to

admissions standards.

EPI BRIEFING PAPER #356 | FEBRUARY 28, 2013 PAGE 24

16. CSUEB, formerly California State University at Hayward,

is a member of the 23-campus, public CSU system.

17. Some of these studies also find an association between

H-1B and American patenting.

18. The squared term was included on the assumption that the

propensity of working in R&D may first rise then later fall

with age.

19. Carnevale, Smith, and Melton (2011) claims a shortage,

citing “rising wages,” but supplies no data to the support the

assertion.

20. See also Freeman (2006).

21. Back in 1998 Congress, accepting the industry’s claim that

older tech workers’ employment difficulties are due to lack of

newer skills, added a user fee that employers of H-1Bs must

pay into a retraining fund. This failed to reduce H-1B usage

(Vaas 2000), not surprising in light of the Wadhwa remark

above—even if the skills issue were not a pretext, in the end

a retrained expensive older programmer would still be an

expensive older programmer. See Matloff (2003 and 2006)

for more details on the age and skills issues.

22. The O-1 visa is for “individuals who possess extraordinary

ability in the sciences, arts, education, business, or athletics,

or who have a demonstrated record of extraordinary

achievement in the motion picture or television industry and

have been recognized nationally or internationally for those

achievements.” See “O-1 Visa: Individuals With

Extraordinary Ability or Achievement,” USCIS, available at

http://www.uscis.gov/portal/site/uscis/

menuitem.eb1d4c2a3e5b9ac89243c6a7543f6d1a/

?vgnextoid=

b9930b89284a3210VgnVCM100000b92ca60aRCRD&

vgnextchannel=

b9930b89284a3210VgnVCM100000b92ca60aRCRD.

23. See Matloff (2012) for data on the rates that Cisco, Intel,

Microsoft, and other mainstream firms made use of a certain

loophole in the prevailing wage law.

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